An intriguing article. To look at an RBF kernel as a low pass filter is something novel. It also basically shows why RBF kernels work brilliantly on high dimensional images. Given that your image features generally lie in a continuous domain, an RBF kernel generally can fit smooth solutions and thereby create more relevant separating hyperplanes,especially in case of multiple classes.